Risk factors for lymph node metastasis in early gastric cancer without lymphatic invasion after endoscopic submucosal dissection

Risk Factors for Lymph Node Metastasis in a Western Series of Patients with Distal Early Gastric Cancer

Background: Assessment of potential lymph node metastasis is mandatory in the appropriate treatment of early gastric cancers. This study analysed factors associated with lymph node metastasis to identify differences between node-negative and node-positive patients and between T1a and T1b cancers. Methods: The clinicopathological features of 129 early gastric cancer patients who had undergone radical gastrectomy were analysed to identify predictive factors for lymph node metastasis. Results: Lymph node metastasis was detected in 76 (59.0%) patients. Node-positive patients were younger (58.1 ± 11.3 years) than those without metastasis (61.9 ± 9.6 years, p = 0.02). Greater tumour sizes were observed in patients with lymph node metastasis (3.6 ± 1.0 cm) compared to node-negative patients (1.9 ± 0.5 cm, p = 0.00001). Depressed form, ulceration, diffuse histological type, and undifferentiated lesions were more frequent in node-positive patients than in the node-negative group. Tumour size > 3.0 cm showed a correlation with lymph node metastasis in both T1a (p = 0.0001) and T1b (p = 0.006) cancer. The male sex (p = 0.006) had a significant correlation with lymph node metastasis in T1a cancer. Depressed appearance (p = 0.02), ulceration (p = 0.03), differentiation (p = 0.0001), diffuse type (p = 0.0002), and lower third location (p = 0.005) were associated with lymph node metastasis in T1b cancer. Conclusions: Tumour size > 3 cm, undifferentiated lesions, ulceration, diffuse type, lower third location, and submucosal invasion are risk factors for lymph node metastasis in early gastric cancer.

Curative criteria for endoscopic treatment of gastric cancer

Endoscopic treatment, particularly endoscopic submucosal dissection, has become the primary treatment for early gastric cancer. A comprehensive optical assessment, including white light endoscopy, image-enhanced endoscopy, and magnification, are the cornerstones for clinical staging and determining the resectability of lesions. This paper discusses factors that influence the indication for endoscopic resection and the likelihood of achieving a curative resection. Our review stresses the critical need for interpreting the histopathological report in accordance with clinical guidelines and the imperative of tailoring decisions based on the patients' and lesions' characteristics and preferences. Moreover, we offer guidance on managing complex scenarios, such as those involving non-curative resection. Finally, we identify future research avenues, including the role of artificial intelligence in estimating the depth of invasion and the urgent need to refine predictive scores for lymph node metastasis and metachronous lesions.

Risk factors associated with lymph node metastasis in early-stage distal gastric cancer

OBJECTS

This study was designed to explore the risk factors of lymph node metastasis (LNM) in distal gastric cancer with early stage, and to provide reference for the choice of treatment protocols.

METHODS

In this retrospective observational study, 824 early distal gastric cancer (EDGC) cases who treated at our unit from 2010 to 2020 were selected as research objects. Subsequently, univariate and multivariate logistic regression analyses were conducted to investigate the associations between LNM and clinicopathological features.

RESULTS

Of these 824 EDGC cases, 140 (17.0%) developed LNM, including 72 N1 stage and 68 N2-3 stage LNM. Multivariate logistic regression analysis identified the tumor diameter ≥1.75 cm (odds ratio (OR) = 2.361, p < 0.001), tumor location (OR = 1.552, p = 0.046), histological classification (p = 0.004), tumor infiltration depth (OR = 2.154, p = 0.001), and vascular infiltration (OR = 4.354, p < 0.001) as independent predictors for LNM. Logistic regression analyses based on 756 N0-1 LNM cases identified the smoking history (OR = 0.507, p = 0.043), tumor diameter ≥1.75 cm (OR = 2.265, p = 0.010), tumor location (OR = 1.834, p = 0.036), histological classification (p = 0.018), tumor infiltration depth (OR = 1.939, p = 0.034), and vascular infiltration (OR = 3.225, p < 0.001) as independent predictors for N1 LNM. Moreover, preoperative hypoalbuminemia (OR = 7.087, p = 0.015), significant preoperative weight loss (OR = 2.724, p = 0.023), tumor diameter ≥1.75 cm (OR = 5.484, p = 0.001), multiple tumors (OR = 9.986, p = 0.038), histological classification (p = 0.029), and vascular infiltration (OR = 33.704, p < 0.001) were proved to be associated with LNM for T1a tumors.

CONCLUSIONS

The tumor diameter, location and infiltration depth, histological classification, and vascular infiltration were expected to be used as predictors of LNM in EDGC, and preoperative hypoalbuminemia, significant weight loss, tumor diameter and number, histological classification, and vascular infiltration were associated with LNM for T1a tumors.

[Fluorescence lymphoscopy with sentinel lymph node biopsy in research of lymphatic flow in early gastric cancer]

OBJECTIVE

To analyze the incidence and risk factors of regional lymph node metastatic lesions, as well as patterns of lymphatic drainage in early gastric cancer using indocyanine green (ICG).

MATERIAL AND METHODS

A prospective single-center non-randomized study included 67 patients with early gastric cancer between 2016 and 2019. All patients underwent endoscopic dissection or surgical resection with sentinel lymph node biopsy.

RESULTS

Regional lymph node metastatic lesions were detected in 12 (20.2%) out of 59 patients with examined lymph nodes. Of these, 11 out of 12 patients had sentinel lymph node lesion, and only 1 patient had metastasis outside this lymph node. The proposed technique for sentinel lymph node biopsy demonstrated high sensitivity, specificity and accuracy (93.2%, 100% and 98.3%, respectively). Risk factors for metastasis of early gastric cancer to regional lymph nodes were high grade adenocarcinoma (p=0.038) and tumor of anterior gastric wall (p=0.013). All patients with tumors of the upper third of the stomach had sentinel lymph node in the left gastric artery basin. Lymph flow was multidirectional in patients with tumors of the middle third of the stomach. In tumors of the lower third of the stomach, sentinel lymph node was located in the right gastroepiploic artery (50%) and left gastric artery basins (36.84%) (p=0.002). Sentinel lymph node was located in the left gastric artery basin in 84% of patients with tumors of the lesser curvature (p<0.001). Lymphatic drainage was multidirectional if tumors were localized on anterior and posterior walls, as well as on the greater curvature.

CONCLUSION

The proposed technique for sentinel lymph node biopsy demonstrated high sensitivity, specificity and accuracy (93.2%, 100% and 98.3%, respectively). ICG is valuable to identify the first lymph node in lymphatic drainage pathway in 83.6% of cases that makes it possible to assess the regional lymphatic collector. In addition, sentinel lymph node biopsy with ICG contributes to analysis of lymphatic drainage in early gastric cancer. The last one has both scientific and practical significance.

Prediction of lymph node metastasis in early gastric signet-ring cell carcinoma: A real-world retrospective cohort study

BACKGROUND

Signet-ring cell carcinoma (SRCC) was previously thought to have a worse prognosis than other differentiated gastric cancer (GC), however, recent studies have shown that the prognosis of SRCC is related to pathological type. We hypothesize that patients with SRCC and with different SRCC pathological components have different probability of lymph node metastasis (LNM).

AIM

To establish models to predict LNM in early GC (EGC), including early gastric SRCC.

METHODS

Clinical data from EGC patients who had undergone gastrectomy at the First Affiliated Hospital of Nanjing Medical University from January 2012 to March 2022 were reviewed. The patients were divided into three groups based on type: Pure SRCC, mixed SRCC, and non-signet ring cell carcinoma (NSRC). The risk factors were identified through statistical tests using SPSS 23.0, R, and Em-powerStats software.

RESULTS

A total of 1922 subjects with EGC were enrolled in this study, and included 249 SRCC patients and 1673 NSRC patients, while 278 of the patients (14.46%) presented with LNM. Multivariable analysis showed that gender, tumor size, depth of invasion, lymphovascular invasion, ulceration, and histological subtype were independent risk factors for LNM in EGC. Establishment and analysis using prediction models of EGC showed that the artificial neural network model was better than the logistic regression model in terms of sensitivity and accuracy (98.0% vs 58.1%, P = 0.034; 88.4% vs 86.8%, P < 0.001, respectively). Among the 249 SRCC patients, LNM was more common in mixed (35.06%) rather than in pure SRCC (8.42%, P < 0.001). The area under the ROC curve of the logistic regression model for LNM in SRCC was 0.760 (95%CI: 0.682-0.843), while the area under the operating characteristic curve of the internal validation set was 0.734 (95%CI: 0.643-0.826). The subgroups analysis of pure types showed that LNM was more common in patients with a tumor size > 2 cm (OR = 5.422, P = 0.038).

CONCLUSION

A validated prediction model was developed to recognize the risk of LNM in EGC and early gastric SRCC, which can aid in pre-surgical decision making of the best method of treatment for patients.

Endoscopic Resection of Early Gastric Cancer and Pre-Malignant Gastric Lesions

Early gastric cancer comprises gastric malignancies that are confined to the mucosa or submucosa, irrespective of lymph node metastasis. Endoscopic resection is currently pivotal for the management of such early lesions, and it is the recommended treatment for tumors presenting a very low risk of lymph node metastasis. In general, these lesions consist of two groups of differentiated mucosal adenocarcinomas: non-ulcerated lesions (regardless of their size) and small ulcerated lesions. Endoscopic submucosal dissection is the technique of choice in most cases. This procedure has high rates of complete histological resection while maintaining gastric anatomy and its functions, resulting in fewer adverse events than surgery and having a lesser impact on patient-reported quality of life. Nonetheless, approximately 20% of resected lesions do not fulfill curative criteria and demand further treatment, highlighting the importance of patient selection. Additionally, the preservation of the stomach results in a moderate risk of metachronous lesions, which underlines the need for surveillance. We review the current evidence regarding the endoscopic treatment of early gastric cancer, including the short-and long-term results and management after resection.

Construction and validation of a novel nomogram to predict cancer-specific survival in patients with gastric adenocarcinoma

Background and aims

Adenocarcinoma is one of the most common pathological types of gastric cancer. The aims of this study were to develop and validate prognostic nomograms that could predict the probability of cancer-specific survival (CSS) for gastric adenocarcinoma (GAC) patients at 1, 3, and 5 years.

Methods

In total, 7747 patients with GAC diagnosed between 2010 and 2015, and 4591 patients diagnosed between 2004 and 2009 from the Surveillance, Epidemiology, and End Results (SEER) database were included in this study. The 7747 patients were used as a prognostic cohort to explore GAC-related prognostic risk factors. Moreover, the 4591 patients were used for external validation. The prognostic cohort was also divided into a training and internal validation sets for construction and internal validation of the nomogram. CSS predictors were screened using least absolute shrinkage and selection operator regression analysis. A prognostic model was built using Cox hazard regression analysis and provided as static and dynamic network-based nomograms.

Results

The primary site, tumor grade, surgery of the primary site, T stage, N stage, and M stage were determined to be independent prognostic factors for CSS and were subsequently included in construction of the nomogram. CSS was accurately estimated using the nomogram at 1, 3, and 5 years. The areas under the curve (AUCs) for the training group at 1, 3, and 5 years were 0.816, 0.853, and 0.863, respectively. Following internal validation, these values were 0.817, 0.851, and 0.861. Further, the AUC of the nomogram was much greater than that of American Joint Committee on Cancer (AJCC) or SEER staging. Moreover, the anticipated and actual CSS values were in good agreement based on decision curves and time-calibrated plots. Then, patients from the two subgroups were divided into high- and low-risk groups based on this nomogram. The survival rate of high-risk patients was considerably lower than that of low-risk patients, according to Kaplan-Meier (K-M) curves (p<0.0001).

Conclusions

A reliable and convenient nomogram in the form of a static nomogram or an online calculator was constructed and validated to assist physicians in quantifying the probability of CSS in GAC patients.

A retrospective analysis based on multiple machine learning models to predict lymph node metastasis in early gastric cancer

Background

Endoscopic submucosal dissection has become the primary option of treatment for early gastric cancer. However, lymph node metastasis may lead to poor prognosis. We analyzed factors related to lymph node metastasis in EGC patients, and we developed a construction prediction model with machine learning using data from a retrospective series.

Methods

Two independent cohorts’ series were evaluated including 305 patients with EGC from China as cohort I and 35 patients from Spain as cohort II. Five classifiers obtained from machine learning were selected to establish a robust prediction model for lymph node metastasis in EGC.

Results

The clinical variables such as invasion depth, histologic type, ulceration, tumor location, tumor size, Lauren classification, and age were selected to establish the five prediction models: linear support vector classifier (Linear SVC), logistic regression model, extreme gradient boosting model (XGBoost), light gradient boosting machine model (LightGBM), and Gaussian process classification model. Interestingly, all prediction models of cohort I showed accuracy between 70 and 81%. Furthermore, the prediction models of the cohort II exhibited accuracy between 48 and 82%. The areas under curve (AUC) of the five models between cohort I and cohort II were between 0.736 and 0.830.

Conclusions

Our results support that the machine learning method could be used to predict lymph node metastasis in early gastric cancer and perhaps provide another evaluation method to choose the suited treatment for patients.

Nomograms Involving HER2 for Predicting Lymph Node Metastasis in Early Gastric Cancer

Objective: We aimed to establish a nomogram for predicting lymph node metastasis in early gastric cancer (EGC) involving human epidermal growth factor receptor 2 (HER2).

Methods: We collected clinicopathological data of patients with EGC who underwent radical gastrectomy and D2 lymphadenectomy at Ruijin Hospital, Shanghai Jiao Tong University School of Medicine between January 2012 and August 2018. Univariate and multivariate logistic regression analysis were used to examine the relationship between lymph node metastasis and clinicopathological features. A nomogram was constructed based on a multivariate prediction model. Internal validation from the training set was performed using receiver operating characteristic (ROC) and calibration plots to evaluate discrimination and calibration, respectively. External validation from the validation set was utilized to examine the external validity of the prediction model using the ROC plot. A decision curve analysis was used to evaluate the benefit of the treatment.

Results: Among 1,212 patients with EGC, 210 (17.32%) presented with lymph node metastasis. Multivariable analysis showed that age, tumor size, submucosal invasion, histological subtype, and HER2 positivity were independent risk factors for lymph node metastasis in EGC. The area under the ROC curve of the model was 0.760 (95% CI: 0.719–0.800) in the training set (n = 794) and 0.771 (95% CI: 0.714–0.828) in the validation set (n = 418). A predictive nomogram was constructed based on a multivariable prediction model. The decision curve showed that using the prediction model to guide treatment had a higher net benefit than using endoscopic submucosal dissection (ESD) absolute criteria over a range of threshold probabilities.

Conclusion: A clinical prediction model and an effective nomogram with an integrated HER2 status were used to predict EGC lymph node metastasis with better accuracy and clinical performance.